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Inventions
Special Issues
Recent Advances and Challenges in Emerging Power Systems: 3rd Edition
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Recent Advances and Challenges in Emerging Power Systems: 3rd Edition

A special issue of Inventions (ISSN 2411-5134). This special issue belongs to the section "Inventions and Innovation in Electrical Engineering/Energy/Communications".

Deadline for manuscript submissions: 31 July 2026 | Viewed by 1287

Special Issue Editor

Prof. Dr. Om P. Malik

E-Mail Website
Guest Editor
Department of Electrical & Computer Engineering, University of Calgary, 2500 University Dr. NW, Calgary, AB T2N 1N4, Canada
Interests: digital protection; adaptive control; control of renewable power generation and microgrids; AI applications in power system control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

This Special Issue follows the publication of the previous editions of “Recent Advances and Challenges in Emerging Power Systems”, consisting of 24 interesting papers.

The continually increasing demand for energy and the pollution caused by the increased generation of electricity using fossil fuels have caused environmental concerns. This has led to the development of renewable energy sources for the generation of electricity and their integration within existing conventional power networks. Differences in the characteristics of the generation of electricity from conventional and renewable energy sources offer challenges, and major restrictions in the operation, control, and protection practices of the entire power network are currently taking place to integrate the two in a seamless and efficient manner. It also offers a tremendous opportunity to rejuvenate the practices that have developed over the past 140 years and enhance the entire grid operation, making it more efficient and reliable in light of the newly developed technologies. A large number of researchers worldwide are now working on developing new ideas and schemes from this perspective, and significant advances in emerging power systems are being made. The objective of this Special Issue of Inventions is to provide a platform where all researchers can contribute their ideas on the integration of conventional power systems and renewable energy sources for the generation of electricity.

Prof. Dr. Om P. Malik
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Inventions is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • renewable energy sources
  • conventional power networks
  • integration of conventional and renewable generation
  • operation, control, and protection of power systems

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Published Papers (2 papers)

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Research

21 pages, 1899 KB  
Article
Risk Assessment of Distribution Network Based on Dirichlet Process Mixture Model and the Cumulant Method
by Yuxuan Huang, Yuwei Chen, Zhenguo Shao, Feixiong Chen, Yunting Shao, Yifan Zhang and Changming Chen
Inventions 2026, 11(2), 42; https://doi.org/10.3390/inventions11020042 - 21 Apr 2026
Viewed by 253
Abstract
To address the increased operational risk in distribution network caused by the grid integration of distributed wind power, a distribution network risk assessment method that combines a Dirichlet process mixture model (DPMM) with the cumulant method (CM) is proposed, to achieve effective quantification [...] Read more.
To address the increased operational risk in distribution network caused by the grid integration of distributed wind power, a distribution network risk assessment method that combines a Dirichlet process mixture model (DPMM) with the cumulant method (CM) is proposed, to achieve effective quantification of operational risk. Firstly, a DPMM is employed to cluster wind power output data, and adaptive kernel density estimation is introduced to construct a probabilistic model of wind power output, thereby improving local fitting accuracy. Secondly, uncertainties arising from wind generation and load are considered, and a probabilistic power flow model for the distribution network is established based on the CM and the Gram–Charlier series expansion, in order to obtain the probability distributions of state variables and branch power flows. Then, distribution entropy theory is introduced to quantify the severity of limit violations for state variables such as voltage and power, so that operational risk assessment is enabled. Finally, simulations are conducted on a modified IEEE 34-bus distribution test system, and the results demonstrate the effectiveness of the proposed method. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 3rd Edition)
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29 pages, 5707 KB  
Article
An ANN-Based MPPT and Power Control Strategy for DFIG Wind Energy Systems with Real-Time Validation
by Hamid Chojaa, Kawtar Tifidat, Aziz Derouich, Mishari Metab Almalki and Mahmoud A. Mossa
Inventions 2026, 11(1), 18; https://doi.org/10.3390/inventions11010018 - 15 Feb 2026
Viewed by 697
Abstract
Doubly Fed Induction Generators (DFIGs) are widely employed in variable-speed wind turbine systems due to their high efficiency, enhanced controllability, and economic viability. This paper presents an intelligent neural-network-based control strategy aimed at maximizing wind energy extraction while ensuring accurate speed regulation of [...] Read more.
Doubly Fed Induction Generators (DFIGs) are widely employed in variable-speed wind turbine systems due to their high efficiency, enhanced controllability, and economic viability. This paper presents an intelligent neural-network-based control strategy aimed at maximizing wind energy extraction while ensuring accurate speed regulation of a DFIG by continuously tracking the maximum power point under fluctuating wind conditions. Two independent control schemes are developed for the decoupled regulation of active and reactive power in a grid-connected DFIG wind turbine. The first scheme is based on conventional field-oriented control using proportional integral regulators (FOC–PI), while the second employs an Artificial Neural Network Controller (ANNC). The effectiveness of both controllers is evaluated through MATLAB/Simulink 2020 Version simulations of a 1.5 MW DFIG-based wind energy conversion system and experimentally validated using a real wind profile implemented on an eZdsp TMS320F28335 digital signal processor. The proposed control approach achieves low output ripple, a steady-state error below 0.16%, total harmonic distortion of 0.38%, and a limited overshoot of 5%. The obtained results confirm the robustness and reliability of the implemented control strategies in enhancing power capture and improving overall system stability under variable wind conditions. Full article
(This article belongs to the Special Issue Recent Advances and Challenges in Emerging Power Systems: 3rd Edition)
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